Pablo Rivas – författare

Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work. Provides practical, step-by-step guides for Earth Scientists who are interested in implementing AI techniques in their work Features case studies to show real-world examples of techniques described in the book Includes additional elements to help readers who are new to AI, including end-of-chapter, key concept bulleted lists that concisely cover key concepts in the chapter

Education must adapt to the Fourth Industrial Revolution. The most advanced countries in the world are all facing the challenge of retraining several generations of workers who are becoming obsolete. The education system has failed them because it hasn't evolved to respond to the advent of the Digital Revolution. It has prepared workers to meet yesterday's challenges, not tomorrow's demands. In Learning to Unlearn, Founder and CEO of Global Alumni, Pablo Rivas, an industry leader in digital education, shows us how the Digital Revolution is tearing down the traditional educational system and transforming the economy, building a brave new world for the 21st century. We already enjoy the best standards of living in human history, with better health, longer life expectancy, and access to the best tools and digital technologies. With freer societies and more global interaction, now is the time to rethink the way we learn how to solve the pressing problems we still face, re-engage those who have been left behind and build the world of tomorrow, not yesterday.

This book constitutes the proceedings of the 30th International Conference on Parallel and Distributed Processing Techniques, PDPTA 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024.The 24 papers included in this book were carefully reviewed and selected from 143 submissions. They have been organized in topical sections as follows: Parallel and distributed processing techniques and applications and HPC and Workshop on Mathematical Modeling and Problem Solving.

This book constitutes the proceedings of the 20th International Conference on Grid, Cloud, and Cluster Computing, GCC 2024, the Third International Conference on Quantum Technologies, ICEQT 2024, and the 21st International Conference on Modeling, Simulation and Visualization Methods, MSV 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024.The proceedings include 15 papers from GCC and ICEQT 2024, which have been selected from a total of 63 submissions. For MSB 2024, the 5 papers included have been accepted from 26 submissions. They have been organized in topical sections as follows: Grid, cloud and cluster computing; emergent quantum technologies; and modeling, simulation and visualization methods.